Determination of positions of objects and in particular of living beings, such as humans or pets, is of increasing interest in many applications. Position estimates may for example be used for the prevention and/or detection of accidents. For example, it may be used to detect that an elderly person has fallen down or that a small child climbs on a table with the risk of falling down. However, estimations of (in particular) positions of creatures in a room may be particularly difficult as the algorithms must take into account that many parameters and characteristics of the environment will be varying with time and/or will be unknown. For example, the specific characteristics of the object that is to be detected may be unknown, and the different objects present in the room may not only vary with time but may also be unknown to the algorithm.
In order to monitor a room for e.g. the purpose of accident prevention, it would be ideal to obtain and analyse a complete picture of what is happening in the room. Such a complete picture may be obtained from one or more video cameras that capture a dynamic image of the desired area. However, the interpretation of the images from such cameras is very complex, and in particular it is very difficult to reliably identify the image segments corresponding to the objects of interest (such as human beings). This may specifically be difficult as the characteristics of the objects, such as the position in the room, will be unknown to the algorithm. Further, the image objects corresponding not only to the objects of interest but also to other objects in the room will tend to be very complex and the correct analysis and evaluation of these objects will tend to require very complex processing and lead to unreliable results.
An example of a video system is presented in US patent publication 2009/0121017. In the system, inventory items are positioned in front of a wall with a recognisable optical pattern. A camera captures the image and detects the amount of exposed surface of the wall by evaluating the area that has the recognisable optical pattern. The amount of exposed surface is then used to determine an amount of the inventory items that are present or missing. However, the system of US patent publication 2009/0121017 merely provides the detection of whether inventory objects are present or not and thus provides only a minimum of information.
Hence, an improved system for determining a depth position for an object in a room would be advantageous and in particular a system allowing increased flexibility, or increased reliability, or facilitated implementation and/or operation, or improved adaptability to dynamic variations and/or improved performance would be advantageous.